From the Publisher
Q: You say these techniques work for "any size business". How can that be? What kind of business does it work for?
A: The Drilling Down approach uses customer activity profiling. Online customer behavior is pretty much the same in a small or large business scenario; if visits or purchases are important to the profitability of the business, the Drilling Down approach works.
The tools used by each size of business are different, not the ideas driving their use. For example, a small business may be using MS Excel or Access to keep track of customers, and a large business would be using a CRM app. The small business would be exporting targeted customers to a file; large business would be using the Drilling Down ideas to build rules for the CRM engine.
That said, the Drilling Down approach is probably least useful in very high ticket B2B shops, where sales cycles are quite long and usually handled by salespeople. Drilling Down is a "direct to customer" approach, and works particularly well in online content publishing and retailing.
Q: What's an "activity-based" profile, and why is it important?
A: Activity-based profiles or models are more powerful than demographic profiles because they are about "action", they attempt to predict the future. Will the customer visit again? Will they buy again? Will they respond to a promotion? These are the types of questions activity-based profiles answer. You will not get these answers from knowing a customer is 45 years old, lives in New York, and likes cats.
That said, adding demographics to an activity-based profile can be very powerful, because the demos supply some of the answers to "why" the customer may behave in the way predicted by the activity-based profile. This allows you to write better copy for promotions and more carefully target groups of customers.
Q: What kind of customer data do I need?
A: The least data you need is a group of customer transactions from a single source (purchases or visits, for example) having a date of the activity and customer identifier of some kind. Any data you have beyond this just improves your ability to profile your customers.
Q: What methods does Drilling Down use?
A: Drilling Down uses derivations of the RFM method developed in cataloging and TV shopping for predicting the likelihood of a customer responding to promotions and judging a customer's value to the company. There are three important differences though. First, the original RFM model is a "one shot" model, taking a snapshot of customer behavior at a point in time. The Drilling Down method looks at customer behavior over time (Customer LifeCycles), which greatly improves on the original model. Second, interactive customers behave differently than offline customers, so the "classic" RFM approach has to be modified for use on the 'Net. Third, the original RFM model is difficult for people without a background in database marketing to deal with. The Drilling Down method simplifies the process to make it easy for people new to data-driven marketing to use, and adds the capability of using visual displays (graphs and charts) of customer behavior to aid in decision making.
Q: Why is the Drilling Down approach unique?
A: Most books or articles on the Latency, Recency, and RFM models are difficult to digest and hard to follow. They show you the theory but don't teach you how to actually construct and implement High ROI Customer Marketing campaigns yourself. This book shows you how to profile and segment or score customers, step by step, in simple language, with a spreadsheet (or any other program you want to use or write yourself to do the scoring - the business rules are provided). Then it shows you how to use the results like the big guys do to increase profits!
This is just where it starts, though. This book extends the basic theories of RFM into a number of tools you can use to improve customer retention, measure the effectiveness of content changes to your site, put a valuation on your business and more.
Along this journey you will also learn how ROI, LifeTime Value, customer LifeCycles, and all the other little gems of data-driven marketing link together for a total picture of how marketing with customer data works.
Q: What's the output of all this, what do I get in the end?
A: In the most simplistic case, each customer gets a "score" to start off their profile. This score ranks the likelihood of a customer to respond to a promotion relative to all the other customers, and is a measure of a customer's future value to your business. The score allows you to rank your customers by where they are in the customer LifeCycle. As the book advances, you see how to use these scores in a lot of different ways, both alone and in combination with any other customer data you may have. The actual "physical" output favored in the book is graphs and charts, so you can "visualize" customer retention and defection, and pick targets for marketing campaigns by looking at these graphs and charts.
Q: What if I don't sell anything on my site? Can the book help me?
A: Absolutely. Any activity a customer generates (a visit or download, for example) can be used in profiling. Content only sites can benefit from using profiles to determine who their best customers are, what parts of the site they visit, and what areas could use improvement. Just because a page has high traffic doesn't mean your best customers are using it. What if you found out your "stickiest" customers actually hang out more in a low page volume area? This would have tremendous implications for the site design and content. Profiles can also be used to assess the effectiveness of changes made to the site. There are solid examples of these approaches provided in the book.
From the Author
It doesn't matter if you are large company with lots of resources or a small start-up, whether you are an IT or marketing person, whether your tool of choice is a data warehouse or a spreadsheet, the toughest part about using your customer data to increase sales or reduce costs (or both) is figuring out where to focus your efforts. What data is most important to evaluate? How do I organize the data into reports that make sense to people and are actionable, reports that drive profitable business decisions?
Here is the secret. No matter what your company calls this use of customer data to increase profits - CRM Analytics, Relationship Marketing, Database Marketing, Behavioral Targeting - the three step path to success is:
1. Track customers using simple customer value metrics that really mean something to the profitability of your business, now and in the future
2. Set up early warning reports or automated "trip wires" to alert you to positive or negative changes in these metrics affecting your future sales and profits
3. Launch a marketing or service action with the specific customers flagged by your reports to either increase your sales, reduce your costs, or both
The Drilling Down book teaches you how.